COMPARATIVE ANALYSIS OF GLOBAL DIGITAL ELEVATION MODELS AND ULTRA-PROMINENT MOUNTAIN PEAKS

Global Digital Elevation Models (GDEMs) are datasets of vital importance for regional-scale analysis in areas such as geomorphology, [paleo]climatology, oceanography and biodiversity. In this work I present a comparative assessment of the datasets ETOPO1 (1’ resolution), GTOPO30, GLOBE, SRTM30 PLUS,...

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Main Author: C. H. Grohmann
Format: Article
Language:English
Published: Copernicus Publications 2016-06-01
Series:ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-4/17/2016/isprs-annals-III-4-17-2016.pdf
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spelling doaj-fb4c7d7c71da402682b173be21d878352020-11-25T02:31:38ZengCopernicus PublicationsISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences2194-90422194-90502016-06-01III-4172310.5194/isprs-annals-III-4-17-2016COMPARATIVE ANALYSIS OF GLOBAL DIGITAL ELEVATION MODELS AND ULTRA-PROMINENT MOUNTAIN PEAKSC. H. Grohmann0Institute of Energy and Environment, University of S˜ao Paulo, 05508-010, - S˜ao Paulo, SP, BrazilGlobal Digital Elevation Models (GDEMs) are datasets of vital importance for regional-scale analysis in areas such as geomorphology, [paleo]climatology, oceanography and biodiversity. In this work I present a comparative assessment of the datasets ETOPO1 (1’ resolution), GTOPO30, GLOBE, SRTM30 PLUS, GMTED2010 and ACE2 (30”) against the altitude of the world’s ultra prominent peaks. GDEMs’ elevations show an expected tendency of underestimating the peak’s altitude, but differences reach 3,500 m. None of the GDEMs captures the full range of elevation on Earth and they do not represent well the altitude of the most prominent peaks. Some of these problems could be addressed with the release of NASADEM, but the smoothing effect caused by moving-window resampling can only be tackled by using new techniques, such as scale-adaptative kernels and curvature-based terrain generalisation.http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-4/17/2016/isprs-annals-III-4-17-2016.pdf
collection DOAJ
language English
format Article
sources DOAJ
author C. H. Grohmann
spellingShingle C. H. Grohmann
COMPARATIVE ANALYSIS OF GLOBAL DIGITAL ELEVATION MODELS AND ULTRA-PROMINENT MOUNTAIN PEAKS
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
author_facet C. H. Grohmann
author_sort C. H. Grohmann
title COMPARATIVE ANALYSIS OF GLOBAL DIGITAL ELEVATION MODELS AND ULTRA-PROMINENT MOUNTAIN PEAKS
title_short COMPARATIVE ANALYSIS OF GLOBAL DIGITAL ELEVATION MODELS AND ULTRA-PROMINENT MOUNTAIN PEAKS
title_full COMPARATIVE ANALYSIS OF GLOBAL DIGITAL ELEVATION MODELS AND ULTRA-PROMINENT MOUNTAIN PEAKS
title_fullStr COMPARATIVE ANALYSIS OF GLOBAL DIGITAL ELEVATION MODELS AND ULTRA-PROMINENT MOUNTAIN PEAKS
title_full_unstemmed COMPARATIVE ANALYSIS OF GLOBAL DIGITAL ELEVATION MODELS AND ULTRA-PROMINENT MOUNTAIN PEAKS
title_sort comparative analysis of global digital elevation models and ultra-prominent mountain peaks
publisher Copernicus Publications
series ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
issn 2194-9042
2194-9050
publishDate 2016-06-01
description Global Digital Elevation Models (GDEMs) are datasets of vital importance for regional-scale analysis in areas such as geomorphology, [paleo]climatology, oceanography and biodiversity. In this work I present a comparative assessment of the datasets ETOPO1 (1’ resolution), GTOPO30, GLOBE, SRTM30 PLUS, GMTED2010 and ACE2 (30”) against the altitude of the world’s ultra prominent peaks. GDEMs’ elevations show an expected tendency of underestimating the peak’s altitude, but differences reach 3,500 m. None of the GDEMs captures the full range of elevation on Earth and they do not represent well the altitude of the most prominent peaks. Some of these problems could be addressed with the release of NASADEM, but the smoothing effect caused by moving-window resampling can only be tackled by using new techniques, such as scale-adaptative kernels and curvature-based terrain generalisation.
url http://www.isprs-ann-photogramm-remote-sens-spatial-inf-sci.net/III-4/17/2016/isprs-annals-III-4-17-2016.pdf
work_keys_str_mv AT chgrohmann comparativeanalysisofglobaldigitalelevationmodelsandultraprominentmountainpeaks
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